ML in PL

Cheng Zhang – Causal Decision Making | ML in PL 22

Panel Discussion – Popularization of ML Research | ML in PL 22

Interactive sequential analysis of a model improves the performance of human decision-making

Lightweight Conditional Model Extrapolation for Streaming Data under Class Prior Shift (LIMES)

A. Osowska-Kurczab & J. Szczerbiński (Allegro) – Retrieval At Scale | ML in PL 22

Matthias Bethge – Brain-like visual representations, decision making, and learning | ML in PL 22

Automated Harmful Content Detection Using Grammar-Focused Representations of Text Data | ML in PL 22

Uncertainty estimation in BERT-based Named Entity Recognition | ML in PL 22

Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with Backprop

Panel Discussion: Industry and Academia | ML in PL 22

Adam Furmanek (Amazon) – Challenges and evolution of Alexa Text-To-Speech | ML in PL 22

Sebastian Jaszczur – Fine-Grained Conditional Computation in Transformers | ML in PL 22

Volodymyr Saviak-Hewlett Packard Enterprise Tools for the AI/ML Development & Training | ML in PL 23

Thea Klaeboe Aarrestad - Unlocking the Secrets of the Universe: ML at CERN | MLSS Kraków 2023

Przemysław Spurek - Hypernetwork approach to generating 3D objects | MLSS Kraków 2023

Agnieszka Grabska-Barwińska - Neuroscience-inspired analysis of machine learning

Christoph Weniger - Simulation-based inference for large forward models | MLSS Kraków 2023

Tomasz Grel (Nvidia): Faster Deep Learning with mixed precision and multiple GPUs

Alexei Efros - Self-Supervised Visual Learning and Synthesis